Spectrometers are in common use as analytical instruments to produce spectra characteristic of atomic or molecular species. One type of spectrometer utilizes an inductively coupled plasma (ICP) such as described in U.S. Pat. No. 4,766,287 of the present assignee. An analyte, i.e. a sample of matter, is injected into the plasma, and the instrument including a monochromator generates a spectrum based on emission from the plasma characteristic of the analyte. A particular spectral peak is generally utilized for measurement to determine presence and quantity of a species in the analyte. Modern instruments have computerized data stations for operating the instrument and performing such functions as calibration and standardization, as described in U.S. Pat. No. 4,893,259, also of the present assignee.
When measuring emission intensity in the ICP to infer analyte concentration, one measures the intensity of the analyte peak superimposed upon a background of non-analyte emission. This non-analyte emission is detrimental to the measurement for two reasons: It contributes to the photon shot noise associated with the measurement, degrading the signal-to-noise; and it can constitute a large part of the gross signal, such that even a small shift in the background signal may create a large relative error in concentration. The degradation of the signal-to-noise ratio of the measurement (and hence detection limits) due to the additional shot noise resulting from the background interference on the signal is unavoidable and cannot be compensated for. The effect of background shifts on apparent analyte concentration can, however, be compensated for by the separation of the net analyte signal from the gross, measured emission signal. Background emission in the ICP has been characterized as arising from such sources as continuum radiation, stray light, recombination spectra, and line broadening.
Background level in the spectrum generally is determined in one of two ways. One is to generate spectra without the analyte and utilize these in calibration for subtraction from the desired spectrum of the analyte. This approach does not account for time variations in the plasma, effects from analyte solvent, or other such variations. Another way is direct measurement of background in the spectrum of interest at one or preferably two selected wavelengths displaced from the selected peak of the analyte. This requires some method such as operator judgement to avoid picking wavelengths where other non-background peaks occur, such as from another species.
In an application of the second method, utilized in ICP instruments such as the Plasma II spectrometer produced and sold by The Perkin-Elmer Corporation, a "heuristic" analysis is applied to a spectrum by way of an algorithm. This automates background estimation by selecting two wavelengths using heuristic rules or rules-of-thumb. Briefly, this operates as follows: The measured spectrum is smoothed to enhance the signal-to-noise ratio; the second derivative of the smoothed spectrum is calculated; zero crossings of the second derivative are tabulated; the different spectral regions are identified by their "signatures", according to densities of zero crossings; candidate wavelengths are selected with heuristic rules; the candidates are scored with the rules; and the best two scoring wavelengths are selected to estimate the background intensity at the analyte wavelength. The candidate wavelengths will have a high number of clustered zero crossings, reflecting lack of a particular peak at these wavelengths.
The heuristic approach has been quite useful, but results in a small but real positive error or bias in background estimation, and there are significant occurrences of catastrophically erroneous estimations when large non-analyte features are present. It also is sensitive to instrument bandpass and number of data in a bandpass.
Another method is disclosed in "A New Baseline Correction Algorithm Using Objective Criteria" by J. Liu and J. L. Koenig, Applied Spectroscopy 41, 447-449 (1987). Spectral background data are fitted to a curve by least squares, and points are rejected whose values are a standard error of estimate or more above the line. The fitting is performed again with the remaining data points. The procedure is repeated until the changes in the estimated parameters are within some preset tolerances or until the number of data points is less than a selected number.